Computer software tools have become indispensable to managing the complexity entailed in designing and manufacturing many modern products. Automobiles are one example of such products.
One aspect of the complexity involved in the design and manufacture of an automobile is the great number and variability of its constituent parts. Typically an automobile model is assembled from a catalogue of parts according to a particular set of design specifications. Because of the number and variability of parts, it can be difficult for designers to ensure that the combinations of the parts are correct.
An approach that uses a computer-based system and associated software to help manage this aspect of complexity is described in U.S. Pat. No. 6,233,094 ('094). As described in the '094 patent, a complex product such as an automobile may be represented in terms of a hierarchical data structure. A top or highest node of the data structure represents the end product (e.g., a compact car), while lower or subordinate nodes represent the components of the end product and associated production processes. A data structure of this kind, used in conjunction with, for example, a graphical user interface (GUI) with various different “views” tailored to specific user needs, helps to simplify design and production.
More specifically, the GUI may enable users, e.g., designers, to specify particular values for characteristics of a desired end product. The characteristics act to select particular variants of components of the end product. That is, a component may be represented in terms of its function within a product or as an abstraction of materials that may be used for the component, and there may be a number of possible variants associated with the component. The variants may be actual concrete realizations of the function or abstraction of the component: for example, one concrete realization of a component abstracted as a “seat” could be a leather, bucket seat, while another might a be a vinyl, bench-type seat. Based on the characteristics of a desired end product, only one of these realizations might be suitable for inclusion in the end product.
The foregoing is a very simple example; in actual practice, there may be hundreds or thousands of components and associated variants within a node hierarchy. Accordingly, there is a need to ensure that the selection of variants is correct: i.e., that it does not result, for example, in different variants being selected for the same component, or in incompatible components being combined. One way in which this need is addressed in the art is to provide user-defined “selection conditions” associated with component variants. A selection condition defines a set of conditions under which a particular variant of a component may be selected for inclusion into a product.
In a design and manufacturing process for a complex product such as an automobile, such selection conditions are typically very numerous, and change frequently. To prevent errors, the selection conditions need to be “consistent” and “complete,” meaning, as explained in more detail further on, that at least one and at most one variant of a component should be selected. To ensure consistency and completeness, a software-implemented method used in the prior art evaluates a group of selection conditions for compliance with a set of rules and constraints. However, this prior art method uses a two-step process that first converts selection conditions into a somewhat lengthy and cumbersome form of logical expression, and then applies constraints to the converted expressions. Execution of the method can be comparatively slow, especially as the number of selection conditions increases. This may be frustrating to users when selection conditions change frequently, as they typically do.
In view of the foregoing considerations, an approach is needed to more efficiently evaluate selection conditions for consistency and completeness.